The first thing that came to my mind when I enroll in Biostat course was to deal with lots of computations, numbers, complex formulas, and etc. However, as we tackle on the different lessons on Biostat, I learned to appreciate it, and I was able to get lots of techniques and ideas which I can apply in my own research topic. Especially when we did our research paper critic, I realized that not all published journals are reliable. In fact, I became more aware and meticulous in choosing journals as basis for my own research topic, because I do not want to repeat the same mistakes done by previous studies. For me, it is very important that researchers like us know how to critic a journal. Another thing I learned in this course before starting an experiment was to clearly know what is the problem statement, what are the hypotheses, and what are the objectives of this experiment or study. Starting an experiment without clearly knowing the problem statement may lead to vague hypotheses and objectives, and sometimes lead to inaccurate experimental design. Failed experiments compromise not only your time but also your effort and money. For me, allowing students to explore and critic a journal was very effective, particularly in honing their skills in planning a good research design. The good thing after I took this course and learned how to critic a paper, I was able to get more interested in attending thesis proposals and thesis defense, which I can apply my learnings.
Honestly, I do not have in depth knowledge in the specific components in doing a research study until I enrol in this course. My knowledge in doing the experiment is very limited but when I learned the different things to consider in planning a research study, I became more confident to do my own research topic. The things like identifying what are my experimental unit or sampling unit and experiment material, what are my sampling designs, how to model my process and system including the treatments and responses during the experiment, how to do true replication, and what are my target variables are very important ingredients in performing experiments, which I just learned in this course. For me, having a good data set after a successful experiment is already an excellent start and a bonus, because there are lots of statistical analysis to explore and apply. Data without analysis is just a number with no implication. By learning the different statistical analysis, I realized that statistical analysis is one important factor to produce a reliable result for a research study. A good data and correct statistical analysis can help researchers infer what is happening around us. Also by considering good research practices, misleading results will be prevented.
Requiring us to do a PLP (Personal Learning Portfolio) is also a good area to start practicing my learnings from this course and develop my skills in doing statistical analysis. By doing the required PLP, I was able to know in detail the different codes and functions important in R studio, and I was able to apply and understand it. During class hours and due to time constraint, the exercises given to us was overlooked most of the time, but with this PLP, I had the chance to understand each details and correct my mistakes. To be honest, I started to like doing stuffs in R studio, especially whenever I try to input a code and got a result. The benefit also of this PLP was to help me recall our lessons more efficiently than doing an exam, and I will be able to read through it even after the end of this course. No more pressure for memorization just more on practice and familiarization, which I think is an effective way to learn. I just realized that when the time comes that I become also a mentor, I will follow this kind of approach because students can still have access to the things they learned from school and apply it to whatever career track they have in the future. The skills and learnings I acquired by doing this PLP will not be for short term memory only, but this can serve as my basis and guide in the field of research.